Food contamination is one of the most significant issues of the modern world, with polluted water, degraded soil, and unsafe manufacturing practices being the biggest threats to food safety. While the world struggles to improve water and soil quality, food safety practices throughout the production and supply chain stages can significantly improve the quality of food safety.
Commitment to safety is arguably the most critical point that can make or break a brand, especially when it comes to the food industry. For food manufacturing companies, having trust in their consumers is a great asset. Even the slightest errors in a production line can cause a product recall, which negatively impacts the brand’s image and future purchases
This case study explains how our client has benefited from a data-driven approach to drip pipe drilling. By using artificial intelligence (AI) they have been able to improve quality while reducing costs and improving safety.
Finding label errors is a challenge for manufacturing companies. Many labels are used in food manufacturing, from variable information laser printed labels to graphics-intensive, pressure-sensitive labels. Even with advancements in labeling technologies, label error still exists on a large scale and is a major concern for manufacturers. In our blog you will know how to find label errors with an automated visual inspection.
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